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NASA NTRS1981

Defining the subjective experience of workload

Flight scenarios that represent different types and levels of pilot workload are needed in order to conduct research about, and develop measures of, pilot workload. In order to be useful, however, the workload associated with such scenarios and the component tasks must be determined independently. An initial study designed to provide such information was conducted by asking a panel of general aviation pilots to evaluate flight-related tasks for the overall, perceptual, physical, and cognitive workload they impose. These ratings will provide the nucleus for a data base of flight-related primary tasks that have been independently rated for workload to use in workload assessment research.

Hart, S. G.↗

NASA NTRS1984

Classification Systems for Individual Differences in Multiple-task Performance and Subjective Estimates of Workload

Human factors practitioners often are concerned with mental workload in multiple-task situations. Investigations of these situations have demonstrated repeatedly that individuals differ in their subjective estimates of workload. These differences may be attributed in part to individual differences in definitions of workload. However, after allowing for differences in the definition of workload, there are still unexplained individual differences in workload ratings. The relation between individual differences in multiple-task performance, subjective estimates of workload, information processing abilities, and the Type A personality trait were examined.

Damos, D. L.↗

NASA NTRS1984

Pilot errors as a source of workload

A pilot opinion survey was conducted to develop a database for creating simulation scenarios that impose predetermined levels of pilot workload. Twelve pilots estimated the effect of 163 events and activities (which they had encountered during their previous flying experiences) on performance, effort, workload, and stress. The events, described in the context of flight scenario segments, included control, navigation and communications activities, aircraft and system failures, and pilot errors. In general, workload, stress, and effort ratings were significantly correlated with each other but not with performance ratings; however, some different response patterns were found as a function of flight segment (e.g., workload, stress, and performance, but not effort, ratings varied with flight phase) and type of event. Errors were rated as a significant source of change for workload, stress, and performance, suggesting that errors could be conceptualized as a cause of workload rather than as a symptom.

Hart, S. G.↗

NASA NTRS1986

Effect of time span and task load on pilot mental workload

Two sets of simulations designed to examine how a pilot's mental workload is affected by continuous manual-control activity versus discrete mental tasks that included the length of time between receiving an assignment and executing it are described. The first experiment evaluated two types of measures: objective performance indicators and subjective ratings. Subjective ratings for the two missions were different, but the objective performance measures were similar. In the second experiments, workload levels were increased and a second performance measure was taken. Mental workload had no influence on either performance-based workload measure. Subjective ratings discriminated among the scenarios and correlated with performance measures for high-workload flights. The number of mental tasks performed did not influence error rates, although high manual workloads did increase errors.

Berg, S. L.↗

NASA NTRS1987

The effects of display and autopilot functions on pilot workload for Single Pilot Instrument Flight Rule (SPIFR) operations

An analytical and experimental research program was conducted to develop criteria for pilot interaction with advanced controls and displays in single pilot instrument flight rules (SPIFR) operations. The analytic phase reviewed fundamental considerations for pilot workload taking into account existing data, and using that data to develop a divided attention SPIFR pilot workload model. The pilot model was utilized to interpret the two experimental phases. The first experimental phase was a flight test program that evaluated pilot workload in the presence of current and near-term displays and autopilot functions. The second experiment was conducted on a King Air simulator, investigating the effects of co-pilot functions in the presence of very high SPIFR workload. The results indicate that the simplest displays tested were marginal for SPIFR operations. A moving map display aided the most in mental orientation, but had inherent deficiencies as a stand alone replacement for an HSI. Autopilot functions were highly effective for reducing pilot workload. The simulator tests showed that extremely high workload situations can be adequately handled when co-pilot functions are provided.

Hoh, Roger H.↗

NASA NTRS1989

Brain-wave measures of workload in advanced cockpits: The transition of technology from laboratory to cockpit simulator, phase 2

The present Phase 2 small business innovation research study was designed to address issues related to scalp-recorded event-related potential (ERP) indices of mental workload and to transition this technology from the laboratory to cockpit simulator environments for use as a systems engineering tool. The project involved five main tasks: (1) Two laboratory studies confirmed the generality of the ERP indices of workload obtained in the Phase 1 study and revealed two additional ERP components related to workload. (2) A task analysis' of flight scenarios and pilot tasks in the Advanced Concepts Flight Simulator (ACFS) defined cockpit events (i.e., displays, messages, alarms) that would be expected to elicit ERPs related to workload. (3) Software was developed to support ERP data analysis. An existing ARD-proprietary package of ERP data analysis routines was upgraded, new graphics routines were developed to enhance interactive data analysis, and routines were developed to compare alternative single-trial analysis techniques using simulated ERP data. (4) Working in conjunction with NASA Langley research scientists and simulator engineers, preparations were made for an ACFS validation study of ERP measures of workload. (5) A design specification was developed for a general purpose, computerized, workload assessment system that can function in simulators such as the ACFS.

Horst, Richard L.↗

NASA NTRS1988

Estimation of duration and mental workload at differing times of day by males and females

Two experiments are reported which investigated whether male and female operator duration estimation and subjective workload followed conventional circadian fluctuation. In the first experiment, twenty-four subjects performed a filled time-estimation task in a constant blacked-out, noise-reduced environment at 0800, 1200, 1600, and 2000 h. In the second experiment, twelve subjects performed an unfilled time estimation task in similar conditions at 0900, 1400, and 1900 h. At the termination of all experimental sessions, participants completed the NASA TLX workload assessment questionnaire as a measure of perceived mental workload. Results indicated that while physiological response followed an expected pattern, estimations of duration and subjective perception of workload showed no significant effects for time-of-day. In each of the experiments, however, there were significant differences in durational estimates and mental workload response depending upon the gender of the participant. Results are taken to support the assertion that subjective workload is responsive largely to task-related factors and indicates the important differences that may be expected due to operator gender.

Hancock, P. A.↗

NASA NTRS1989

The effects of practice on tracking and subjective workload

Six college-age male subjects performed one hundred, two-minute trials on a second-order tracking task. After each trial, subjects estimated perceived workload using both the NASA TLX and SWAT workload assessment procedures. Results confirmed an expected performance improvement on the tracking task which followed traditional learning curves within the performance of each individual. Perceived workload also decreased for both scales across trials. While performance variability significantly decreased across trials, workload variability remained constant. One month later, the same subjects returned to complete the second experiment in the sequence which was a retention replication of the first experiment. Results replicated those for the first experiment except that both performance error and workload were at reduced overall levels. Results in general affirm a parallel workload reduction with performance improvement, an observation consistent with a resource-based view of automaticity.

Hancock, P. A.↗

NASA NTRS1990

Crew workload strategies in advanced cockpits

Many methods of measuring and predicting operator workload have been developed that provide useful information in the design, evaluation, and operation of complex systems and which aid in developing models of human attention and performance. However, the relationships between such measures, imposed task demands, and measures of performance remain complex and even contradictory. It appears that we have ignored an important factor: people do not passively translate task demands into performance. Rather, they actively manage their time, resources, and effort to achieve an acceptable level of performance while maintaining a comfortable level of workload. While such adaptive, creative, and strategic behaviors are the primary reason that human operators remain an essential component of all advanced man-machine systems, they also result in individual differences in the way people respond to the same task demands and inconsistent relationships among measures. Finally, we are able to measure workload and performance, but interpreting such measures remains difficult; it is still not clear how much workload is too much or too little nor the consequences of suboptimal workload on system performance and the mental, physical, and emotional well-being of the human operators. The rationale and philosophy of a program of research developed to address these issues will be reviewed and contrasted to traditional methods of defining, measuring, and predicting human operator workload. Viewgraphs are given.

Hart, Sandra G.↗

NASA NTRS1996

Automated clustering-based workload characterization

The demands placed on the mass storage systems at various federal agencies and national laboratories are continuously increasing in intensity. This forces system managers to constantly monitor the system, evaluate the demand placed on it, and tune it appropriately using either heuristics based on experience or analytic models. Performance models require an accurate workload characterization. This can be a laborious and time consuming process. It became evident from our experience that a tool is necessary to automate the workload characterization process. This paper presents the design and discusses the implementation of a tool for workload characterization of mass storage systems. The main features of the tool discussed here are: (1)Automatic support for peak-period determination. Histograms of system activity are generated and presented to the user for peak-period determination; (2) Automatic clustering analysis. The data collected from the mass storage system logs is clustered using clustering algorithms and tightness measures to limit the number of generated clusters; (3) Reporting of varied file statistics. The tool computes several statistics on file sizes such as average, standard deviation, minimum, maximum, frequency, as well as average transfer time. These statistics are given on a per cluster basis; (4) Portability. The tool can easily be used to characterize the workload in mass storage systems of different vendors. The user needs to specify through a simple log description language how the a specific log should be interpreted. The rest of this paper is organized as follows. Section two presents basic concepts in workload characterization as they apply to mass storage systems. Section three describes clustering algorithms and tightness measures. The following section presents the architecture of the tool. Section five presents some results of workload characterization using the tool.Finally, section six presents some concluding remarks.

Pentakalos, Odysseas I.↗

NASA NTRS1998

Workload Characterization of CFD Applications Using Partial Differential Equation Solvers

Workload characterization is used for modeling and evaluating of computing systems at different levels of detail. We present workload characterization for a class of Computational Fluid Dynamics (CFD) applications that solve Partial Differential Equations (PDEs). This workload characterization focuses on three high performance computing platforms: SGI Origin2000, EBM SP-2, a cluster of Intel Pentium Pro bases PCs. We execute extensive measurement-based experiments on these platforms to gather statistics of system resource usage, which results in workload characterization. Our workload characterization approach yields a coarse-grain resource utilization behavior that is being applied for performance modeling and evaluation of distributed high performance metacomputing systems. In addition, this study enhances our understanding of interactions between PDE solver workloads and high performance computing platforms and is useful for tuning these applications.

Waheed, Abdul↗

NASA NTRS1997

Performance Analysis of the NAS Y-MP Workload

This paper describes the performance characteristics of the computational workloads on the NAS Cray Y-MP machines, a Y-MP 832 and later a Y-MP 8128. Hardware measurements indicated that the Y-MP workload performance matured over time, ultimately sustaining an average throughput of 0.8 GFLOPS and a vector operation fraction of 87%. The measurements also revealed an operation rate exceeding 1 per clock period, a well-balanced architecture featuring a strong utilization of vector functional units, and an efficient memory organization. Introduction of the larger memory 8128 increased throughput by allowing a more efficient utilization of CPUs. Throughput also depended on the metering of the batch queues; low-idle Saturday workloads required a buffer of small jobs to prevent memory starvation of the CPU. UNICOS required about 7% of total CPU time to service the 832 workloads; this overhead decreased to 5% for the 8128 workloads. While most of the system time went to service I/O requests, efficient scheduling prevented excessive idle due to I/O wait. System measurements disclosed no obvious bottlenecks in the response of the machine and UNICOS to the workloads. In most cases, Cray-provided software tools were- quite sufficient for measuring the performance of both the machine and operating, system.

Bergeron, Robert J.↗

NASA NTRSDate not supplied

Predictive Workload Model for Air Traffic Controllers during UAM Operations

The effect of airspace factors on air traffic controller (ATC) workload has been an active area of study for almost three decades due to the importance of safety considerations necessary to design and maintain operations. Existing literature has examined several traffic-related (e.g., number of aircraft under control, loss of separation) contributors to ATC workload and proposed mathematical functions to best describe controller response. However, future air traffic continues to increase in complexity with the introduction of urban air mobility (UAM) – or the transportation of humans and cargo using electric vertical takeoff and landing (eVTOL) aircraft. UAM aims to alleviate congestion for existing ground transportation systems and improve mobility within urban centers and other high-demand locations. This shift in the traditional airspace paradigm necessitates an evolved understanding of model use and development for ATC workload prediction. This study aimed to develop an ATC workload forecasting model based on human-in-the-loop (HITL) simulation data for UAM operations at large airports. Data collected from the HITL simulation served as the training and testing data for a Long Short-Term Memory recurrent neural network and enabled time-series forecasting of ATC workload from traffic characteristics. Results demonstrated the potential of LSTM models for forecasting ATC workload 40 minutes into the future and highlighted important considerations for future development.

predictive model↗

NASA NTRSDate not supplied

Predictive Workload Model for Air Traffic Controllers during UAM Operations

predictive model↗

NASA NTRS2016

Task Demand Variation in Air Traffic Control: Implications for Workload, Fatigue, and Performance

In air traffic control, task demand and workload have important implications for the safety and efficiency of air traffic, and remain dominant considerations. Within air traffic control, task demand is dynamic. However, research on demand transitions and subsequent controller perception and performance is limited. This research uses an air traffic control simulation to investigate the effect of task demand transitions, and the direction of those transitions, on workload and fatigue and one efficiency performance measure. Results indicate that a change in task demand appears to affect both workload and fatigue ratings, although not necessarily performance. In addition, participants' workload and fatigue ratings in equivalent task demand periods appear to change depending on the demand period preceding the time of the current ratings. Further research is needed to enhance understanding of demand transition and workload history effects on operator experience and performance, in both air traffic control and other safety-critical domains.

workload history↗

NASA NTRS2016

Task Demand Variation in Air Traffic Control: Implications for Controller Workload, Fatigue, and Performance

In air traffic control, task demand and workload have important implications for the safety and efficiency of air traffic, and remain dominant considerations. Within air traffic control, task demand is dynamic. However, research on demand transitions and subsequent controller perception and performance is limited. This research uses an air traffic control simulation to investigate the effect of task demand transitions, and the direction of those transitions, on workload and fatigue and one efficiency performance measure. Results indicate that a change in task demand appears to affect both workload and fatigue ratings, although not necessarily performance. In addition, participants workload and fatigue ratings in equivalent task demand periods appear to change depending on the demand period preceding the time of the current ratings. Further research is needed to enhance understanding of demand transition and workload history effects on operator experience and performance, in both air traffic control and other safety-critical domains.

workload history↗

DOE OSTI2023

Micromovements and discomfort associated with flight mission with helmet operation tasks with different levels of cognitive workload

When performing stationary tasks under elevated cognitive workload, individuals must perform continual muscle contractions to maintain stability of the body, resulting in fatigue of the postural muscles. When the muscles perform these contractions in a prolonged manner, the body potentially responds through small changes in body movements—micromovements that may lead to discomfort. The study purpose was to evaluate impact of cognitive load on micromovements. The micromovements were measured during three different cognitive workloads; low, medium, and high. The NASA-TLX score was used to evaluate the perceived mental workload and discomfort was assessed by visual analog scale. In total, 60 subjects (30 males and 30 females) were recruited and performed cognitive tasks that simulated flight operations such as changing the radio frequency based on air traffic control messages, balancing the fuel levels in simulated fuel tanks, and aiming a reticle in a designated moving target using the cyclic control. Cognitive load was defined by the frequency of events. Micromovements were defined by changes in the center of pressure (COP) of the seat pan and COP standard deviation. It was found that the high cognitive workloads had the highest NASA-TLX scores including mental demands, temporal demands, and effort. The neck area had the highest overall levels of discomfort followed by upper back. The highest standard deviation for COP shift and number of micromovements occurred for medium cognitive workloads. In conclusion, while there were some interesting trends, few trends reached a statistical significance due to high variability among subjects for the outcome variables.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Union: An Automatic Workload Manager for Accelerating Network Simulation

With the rapid growth of the machine learning applications, the workloads of future HPC systems are anticipated to be a mix of scientific simulation, big data analytics, and machine learning applications. Simulation is a great research vehicle to understand the performance implications of co-running scientific applications with big data and machine learning workloads on large-scale systems. In this paper, we present Union, a workload manager that provides an automatic framework to facilitate hybrid workload simulation in CODES. Furthermore, we use Union, along with CODES, to investigate various hybrid workloads composed of traditional simulation applications and emerging learning applications on two dragonfly systems. The experiment results show that both message latency and communication time are important performance metrics to evaluate network interference. Network interference on HPC applications is more reflected by the message latency variation, whereas ML application performance depends more on the communication time.

heterogeneous workloads↗